Analytics Catalog/Oracle Fusion ERP/Receivables/Automatic Bills Receivable Remittance Execution Report
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Seeded report · Bills receivable

Automatic Bills Receivable Remittance Execution Report

Receivables◆ Seeded · Bills receivable

Reports the process that remits bills receivable to the bank for collection, detailing the bills sent.

Sample build of the Automatic Bills Receivable Remittance Execution Report — reconciled, and rendered tool-neutral so it runs in Power BI, ThoughtSpot, or Tableau.

Automatic Bills Receivable Remittance Execution Report
Sample build · illustrative
Filters
Period
FEB-26
Ledger
US Primary
Currency
USD
180
Bills remitted
$4.20M
Remitted value
6
Rejected
BillCustomerMaturityAmountBank
SampleAcme IndustrialSample$1,240,500.00Sample
Northwind Trading$842,150.75
SampleGlobex HoldingsSample$96,400.00Sample
Initech LLC$1,005,233.10
SampleUmbrella CorpSample$58,720.40Sample
SampleAcme IndustrialSample$1,240,500.00Sample
AI Analyst · active
reading

The report reports the process that remits bills receivable to the bank for collection.

flag

Six bills were rejected at remittance — they won't be collected by the bank this cycle.

root cause & next step

Fix the bill or bank instruction and re-remit; a rejected bill receivable is delayed collection.

Illustrative data. The live interactive version — drill-through, filters, export, and the AI Analyst — runs on your warehouse. See it live →

This is the report's BI Publisher data model — the SQL data set BI Publisher runs against Oracle tables to produce the output. The same SQL becomes a dbt model in your warehouse, so one definition drives both the formatted report and the analytics layer.

Data sources

How it interconnects: this data set reads the physical tables above. Those same tables surface in OTBI as subject areas and in BICC as PVOs — three lenses on one source. Open any table to trace its subject areas and View Objects.
The SQL data set is authored to this report's exact spec during the build and ships as the BI Publisher data model plus a matching dbt model — one definition, both layers.

The data-warehouse model — one fact surrounded by conformed dimensions (what you slice by) and measures (what you aggregate), expressed as dbt so it migrates with you. Grain: one row per source transaction.

AR_TRANSACTION_HISTORY_A…dimensionRA_CUSTOMER_TRX_ALLfact · one row per source transactionAmount
●— fact → dimension join
ElementTypeDefinition
AR_TRANSACTION_HISTORY_ALLdimensiondimension
Amountmeasuremeasure
Runs on your cloud warehouse — Snowflake, BigQuery, Redshift, or Synapse on AWS, Google Cloud, Azure, or any provider. Reconciled to the source control total — 0% variance by design. You own the code, the model, and the data.
How the data gets here: a BICC bulk extract of the source tables above, on the same pattern for every report. See the extraction pattern & data flow →
See the complete model
How this report's fact and dimensions fit the full picture, via conformed keys.
Receivables data model →Enterprise model →

Every source object behind this report. Each linked table has its own page with full column descriptions, drawn from the Oracle BICC lineage and articulated for practitioners.

TableReporting columnsSubject areas
RA_CUSTOMER_TRX_ALL5816
AR_TRANSACTION_HISTORY_ALL131
Reporting columns = fields the report selects that are exposed as analytics attributes; subject areas = the OTBI subject areas the table appears in. Setup and configuration tables (master data, ledger and book setup, lookups) are referenced by the report's joins but aren't exposed as analytics columns or subject areas — that's expected, not a gap.

Customization note  Bills-receivable lifecycle is niche; when relevant, teams track it as a maturity and collection pipeline. Irvine rebuilds these on your data.